1. Technical Field
This invention relates to image processing techniques and, more particularly, to techniques for detecting objects moving through cluttered background.
2. Discussion
A long-standing problem for trackers with imaging sensors is the inability to autonomously acquire objects silhouetted against clutter. In situations where there are objects in the field of view which compete against the object of interest, false acquisitions frequently result. The inability of prior art trackers to perform autonomous acquisition under such conditions has limited the usefulness of those systems.
Much effort has been expended over the past 20 to 30 years to design autonomous acquisition seekers. The results have generally not been successful. The use of spatial discrimination based on clutter power spectral density (Wiener spectra) has been generally unsuccessfully applied to reticle seekers. One of the reasons for the lack of success is that the clutter elements which interfere with the object detection process are the high spatial frequency components (e.g., cloud edges and discrete high contrast objects with dimensions similar to the object of interest). Spatial filters designed with Wiener spectra inevitably result in a bandpass filter which attenuates the low spatial frequencies but is unable to eliminate the clutter components that have high spatial frequency content. Spectral discrimination techniques have been attempted, notably in the infrared, with the detection of the CO2 emission bands known as the blue spike and the red spike. However, these narrow spectral lines do not propagate well in the atmosphere and therefore are attenuated when the propagation path is appreciable. In addition, the narrowness of the emission line implies relatively low signal-to-noise ratio for detection. The inadequacy of signal-to-noise ratio has generally rendered this technique impractical.